Compared to the traditional exposure assessment using ambient monitoring of environmental pollutants, rapid and sensitive detection of large sets of analytes including exogenous chemicals, their metabolites, and other derivatives such as protein adducts (“exposome”, e.g., metabolome and adductome) using human specimens such as blood and urine, which reflect the complexity of exposure in the personal environment, has opened up new opportunities for epidemiologic studies of human exposure. However, two key challenges remain for “exposomics”: (1) rapid and efficient processing of small volumes of biospecimens, especially human blood samples; and (2) detecting multiple and/or multiclass analytes simultaneously with high-sensitivity and high-specificity from such small volumes of biospecimens.
So far, there have been a few methods that have been adopted to directly couple sample processing (e.g., solid-phase extraction (SPE)) with nanoflow liquid chromatography-mass spectrometry (LC-MS) in order to minimize sample loss and increase detection sensitivity. However, these methods usually require substantially large sample volumes for analyzing low concentrations of target analytes, which makes the methods impractical for, e.g., population studies of multiple (multiclass) analytes where only small volumes of samples are collected. Accordingly, there is a need for a platform that may enable sensitive, robust, high-throughput and multiplexed biomonitoring using small volumes of samples.